A. Bigano °, F. Bosello* , R. Roson’, R.S.J. Tol”
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Transcript of A. Bigano °, F. Bosello* , R. Roson’, R.S.J. Tol”
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A. Bigano °, F. Bosello* , R. Roson’, R.S.J. Tol”
Economy Wide Impacts of Climate Change: A Joint Analysis for Sea
Level Rise and Tourism
°Fondazione Eni Enrico Mattei*Università di Milano e Fondazione Eni Enrico Mattei ’Università di Venezia e Fondazione Eni Enrico Mattei ”Free University of Amsterdam, Hamburg University, Carnegie Mellon University, ESRI Dublin
Chronic Risk of Global Climate Change to Urban Coasts and EconomiesStevens Institute of Technology, NJ, 15-16 November 2007
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Introduction: future temperature + SLR
IPCC FAR (2007)
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Introduction: impacts
IPCC FAR (2007)
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Objectives
Evaluate economically climate change impacts with a general equilibrium perspective (first and higher
order welfare costs substitution mechanisms + market interdependencies changes induced by
changes in relative prices)
Initially one category of impact at a time
Then jointly (this study tourism + SLR)
Use and development of a CGE model/approach
Calibrate a climate change damage function accounting for “autonomous economic adaptation”
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Objectives
This approach is innovative
The predominant approach in climate change impact assessment is that of “direct costing” Partial
equilibrium:
Damage = (“price”) x (“quantity”)
This method is usually applied in “SLR studies” see e.g. Nichols et al. (2007) for discussion -> but also in other domains (e.g.
health, agriculture etc.) and to calibrate cc damage functions in global studies (see e.g. Nordhaus (1995, 1999), Manne and
Richels (1995, 2004), Tol (1995 – 2002))
This disregards rebounds and feedback: social economic systems adapt and “shocks” propagate
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Consumers(households, government)
Producers(firms, government)
Maximise welfarefrom consumption
Minimise costof production
supply
demand supply
demand
Input marketsK, L, Land, NR
Income
Income
Output marketsGoods and
services
Constrained by income
Constrained by technology
Demand and supply functions “mimic”
observed economic systems: parameters
are calibrated on “real” data. All markets are
Interdependent.
Sketching a CGE model
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The CGE Model
GTAP-EF(Extended Version of GTAP-E Burniaux and Truong 2002)
16 Regions:USA: United StatesCAN: CanadaWEU: Western Europe JPK: Japan and KoreaANZ: Australia New ZealandEEU: Eastern EuropeFSU: Former Soviet UnionMDE: China and IndiaCAM: Rest of the WorldSAM: South AmericaSAS: South AsiaSEA: South East AsiaCHI: ChinaNAF: North Africa SSA: Sub-Saharan AfricaSIS: Small Island States
17 Sectors:RiceWheatCereal CropsVegetable FruitsAnimalsForestryFishingCoalOilGasOil ProductsElectricityWaterEnergy Intensive industriesOther industriesMarket ServicesNon-Market Services
Calibrated in 1997
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The CGE Model: consumption “tree”
utility
private consumption public consumption savings
item1 item m item1 item m
domestic foreign
region 1 region n
domestic foreign
region 1 region n
Using Income (from endowment ownrship) in
fixed (C-D) shares for:Households max.
Armington
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The CGE Model: production “tree”
output
other inputsv.a.+energy
natural resources
land labour capital+energy domestic foreign
region 1 region ncapital
energy
non-electric electric
dom for
r1 rn
coal
dom for
r1 rn
non-coal
gas oil petrolemum products
dom for
r1 rn
dom for
r1 rn
dom for
r1 rn
CES
Leontieff
Armington
Armington
Min. production cost
CES
CES
CES
CES
Armington
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The CGE Model
Investment
……..
“World Bank”
• Households save a constant share of their income.
……..
• Redistribution mechanism based on the equalization of regional return to capital.
B
A
C F
E
D
REG. 1
REG. 2
REG. 1
REG. 2
REG. nREG. n 1) Investment is Endogenous.
2) A,B,C flows ≠ D,E,F flows.3) A region can run a foreign debt or credit.
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“Benchmarking” the model in the future
Starting point: core model calibrated in 1997.
Necessary to get a future reference case “without climate change” (“Pseudo-calibration” )
This refers to obtaining a picture of the future world economy. In practice, long-run estimates of primary inputs (land, labour, capital
and natural resources) stocks and productivity used to:
Shock the model 1997 calibration equilibrium to obtain future benchmark equilibria ( 2050).
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Data sources for the benchmark
- Population: World Bank.
- Capital stock: G-Cubed model Version48E (McKibbin, 2001).
- Labour stock: G-Cubed model Version48E (McKibbin, 2001).
- Labour productivity: G-Cubed model Version48E (McKibbin, 2001).
- Crops’ productivity: IMAGE 2.2, B1 Scenario (RIVM, 2001).
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Benchmark Assumptions
Capital stock
(initial) Agriculture Energy Electricity ServicesEnergy
Intensive industries
USA 30.4 253.7 249.6 346.3 114 120.1 0 69.5 100 120.1CAN 15.6 186.3 263.7 376.4 225.5 134.1 6.1 80.1 157.6 134.1WEU -3.7 164 266.6 234.7 52.8 140.8 9.4 85.3 177.2 140.8JPK -11.6 177.5 214.5 263.7 162.5 133.6 0 79.8 163.1 133.6ANZ 18.7 184.8 263.7 227.3 225.5 133 6.1 79.4 156.3 133EEU -2.7 260.1 257 460.8 267.3 221.9 47.5 148.3 267.1 221.9FSU -2.7 275.5 257 407.5 267.3 235 50.3 157.1 282.9 235MDE 107.7 373.7 324.2 419 379.9 227.3 48.7 151.9 276.2 227.3CAM 54.9 375.4 352.4 523.8 379.9 287.8 72.8 197.1 330 287.8SAM 51 411.4 352.4 530.8 379.9 315.4 79.7 216 207 315.4SAS 72.6 500.8 254.4 818.8 339.5 346.3 75 237.1 422.9 346.3SEA 68.9 336.7 352.4 560.5 379.9 258.2 65.3 176.8 316.8 258.2CHI 29.4 463.4 254.4 660.5 339.5 251.2 63.5 172 306.7 251.2NAF 127 235.1 352.4 441.9 379.9 180.2 45.6 123.4 221.2 180.2SSA 135.8 375.9 352.4 711.4 379.9 288.2 72.9 197.4 353.7 288.2SIS 49.1 419.9 352.4 572.5 379.9 321.9 81.4 220.4 332 321.9
Land Productivity
Labour Productivity
PopulationLabour stock
Natural Resources
stock
% changes 1997-2050
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Baseline GDP
% changes 1997-2050
0
500
1000
1500
2000
2500
3000
3500
Our
A2
B1
B2
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The Modeling Exercise
SLR (No protection): Land loss is modeled as a negative “supply-side” shock on the endowment LAND (which is an exogenous variable in the model).
Tourism: Changes in tourism demand are modeled as changes in the demand for recreational services (within the market service sector), income flows determined by additional foreign expenditure are modelled.
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Climate Change Scenarios and Models
• T = + 1.2 °C. in 2050 wrt 1980 -1999• SLR= + 25 cm. in 2050
SLR -- > Data set on land loss wrt different sea-level rise scenarios (based on Delft Hydraulics GVA
(1993), Beniston (1998 ), Nicholls (1995), Bijlsma et al. (1996))
Tourism -- > HTM model (Tol et al. 2002): changes in arrival,
departures and expenditures, determined by socio-economic +
environmental drivers (changes in temperature and coastal land
availability)
Environmental Impact Models
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Sea level rise alone
Inputs to the CGE model Outputs from the CGE model
ml $as % of
GDP Land Labour CapitalUSA -0.052 121 0.0002 -0.0013 -0.016 0.015 0.684 -0.034 -0.034
CAN -0.002 72 0.0017 -0.0004 0.029 0.032 0.822 -0.013 -0.009
WEU -0.029 298 0.0005 -0.0019 -0.005 0.016 0.608 -0.035 -0.036
JPK -0.141 146 0.0004 -0.0018 0.006 0.011 1.132 -0.034 -0.035
ANZ -0.010 237 0.0075 -0.0008 0.081 0.010 0.967 -0.022 -0.028
EEU -0.041 45 0.0016 -0.0047 -0.001 -0.037 0.629 -0.074 -0.079
FSU 0.000 0 0.0000 -0.0007 -0.005 0.010 0.613 -0.038 -0.040
MDE -0.007 75 0.0011 -0.0045 0.000 -0.001 0.998 -0.035 -0.044
CAM -0.120 182 0.0049 -0.0098 0.052 -0.023 0.806 -0.053 -0.059
SAM -0.041 647 0.0043 -0.0007 0.102 0.020 0.742 0.005 0.007
SAS -0.396 6000 0.1180 -0.0649 0.078 -0.212 1.420 -0.285 -0.292
SEA -0.839 14913 0.1475 -0.1092 -0.032 -0.357 2.372 -0.468 -0.504
CHI -0.091 579 0.0063 -0.0303 -0.060 -0.236 0.521 -0.235 -0.260
NAF -0.039 1120 0.0548 -0.0036 0.012 0.039 0.795 -0.002 0.016
SSA -0.130 8869 0.2359 -0.0094 0.100 -0.029 1.034 -0.055 -0.062
SIS -0.167 188 0.0220 -0.0189 -0.020 -0.086 0.885 -0.162 -0.169
Terms of Trade
Invest. flows
Factor PricesLand loss
Direct costs: value of land lost
GDP
Reference Year 2050: % changes wrt baselineland loss ranking
direct cost
ranking
gdp loss ranking
USA 8 15 12CAN 15 10 16WEU 12 13 10JPK 4 14 11ANZ 13 6 13EEU 9 11 7FSU 16 16 14MDE 14 12 8CAM 6 8 5SAM 10 9 15SAS 2 3 2SEA 1 2 1CHI 7 7 3NAF 11 4 9SSA 5 1 6SIS 3 5 4
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The difference between direct and general equilibrium cost
0.1475
0.0063
0.0548
0.2359
0.0220
0.0649
0.1092
0.0303
0.0036 0.00940.0189
0.1180
0
2000
4000
6000
8000
10000
12000
14000
16000
SAS SEA CHI NAF SSA SIS
Mill
ion
s $
0.00
0.05
0.10
0.15
0.20
0.25
2050
GD
P %
DC abs GEC abs DC %GDP GEC % GDP
0.00
02 0.00
17
0.00
05
0.00
04
0.00
75
0.00
16
0.00
00 0.00
11
0.00
49
0.00
43
0
100
200
300
400
500
600
700
800
USA CAN WEU JPK ANZ EEU FSU MDE CAM SAM
Mill
ion
s $
0.000
0.002
0.004
0.006
0.008
0.010
0.012
2050
GD
P %
DC abs GEC abs DC %GDP GEC % GDP
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Tourism Alone
Imposed Endogeno
us USA -0.874 -1.259 1.457 -0.365 -0.0015 -0.511 -0.626CAN 0.459 0.755 -1.381 0.211 -0.0004 0.420 -0.116WEU 0.883 1.357 -2.287 0.378 0.0556 0.331 0.238JPK 5.639 8.096 -14.760 2.779 -0.1768 3.768 3.810ANZ -1.530 -2.096 3.475 -0.696 0.0493 -0.063 -0.654EEU -3.172 -4.683 3.255 -1.169 -0.1068 -0.803 -0.999FSU -0.024 -0.073 0.052 -0.011 -0.0311 -0.135 -0.390MDE -5.974 -8.600 8.295 -2.074 0.0030 -2.279 -1.960CAM -5.519 -7.980 7.518 -2.387 -0.1139 -1.030 -1.805SAM -1.521 -2.015 1.583 -0.558 -0.0027 -0.100 -1.161SAS -1.532 -1.794 1.102 -0.453 0.0251 0.596 -0.507SEA -5.452 -7.057 6.854 -1.629 -0.0324 -0.825 -0.620CHI -6.777 -8.020 2.731 -1.129 -0.0442 -1.127 -0.854NAF -3.204 -4.179 1.314 -0.646 -0.1614 -0.795 -0.640SSA -3.068 -4.122 2.993 -1.053 -0.0079 -0.359 -0.951SIS -12.251 -18.984 17.001 -5.990 -0.5330 -7.522 -7.852
Market services demand
Other goods/services dem.
Income transfers
GDP Terms of
TradeInvest. Flows
Reference Year 2050: % changes wrt baseline
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Tourism and sea level jointly
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
USACAN
WEU
JPK
ANZEEU
FSUM
DECAM
SAMSAS
SEACHI
NAFSSA
ROW
-90
-70
-50
-30
-10
10
30
SLR&TOU SLR TOU %D SLR&TOU-SUM
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Conclusions
Using a CGE approach to evaluate climate change impacts is important: huge difference respect to a
partial equilibrium assessment
Interactions among impacts are alslo non-negligible
A lot to do: - improve the quality of input data
- expand the set of impacts considered (on health, energy demand, physical capital, agriculture etc.)
- consider a dynamic setting
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Thank You!